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Cortisol/Adrenocorticotropic Hormone Ratio: A Novel Biomarker for Metabolic Risk Stratification in Obese Patients
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Abstract
Objective
This study investigates the predictive value of the cortisol/adrenocorticotropic hormone (CORT/ACTH) ratio, a quantitative marker of hypothalamic-pituitary-adrenal (HPA) axis function, in assessing metabolic heterogeneity and the risk of type 2 diabetes mellitus (T2DM) in obese patients. By identifying a novel biomarker, this research contributes to metabolic risk stratification and provides a foundation for precise obesity management.
Methods
A retrospective cohort study was conducted involving 210 obese patients (BMI ≥ 28 kg/m²) from the Department of Endocrinology at Jiangsu Second Hospital of Traditional Chinese Medicine, enrolled between September 2022 and September 2023. Fasting plasma cortisol, adrenocorticotropic hormone (ACTH), and metabolic parameters were measured. Participants were stratified by tertiles of the CORT/ACTH ratio. Multivariate logistic regression and restricted cubic spline (RCS) models were used to analyze the associations of the ratio with insulin resistance (IR) and T2DM risk.
Results
①No statistically significant differences were observed among the three groups in gender composition, BMI,homeostasis model assessment of insulin resistance (HOMA-IR), high-density lipoprotein cholesterol (HDL-C), or T2DM prevalence (all P > 0.05), while age showed a gradient decrease with increasing CORT/ACTH ratio (P = 0.004); ② Spearman rank correlation analysis revealed that the CORT/ACTH ratio was significantly positively associated with triglycerides (TG, r = 0.14, P = 0.036) and low-density lipoprotein cholesterol (LDL-C, r = 0.19, P = 0.006), but not with HOMA-IR (r = 0.05, P = 0.456);③The RCS model revealed a non-linear relationship between the CORT/ACTH ratio and HOMA-IR (non-linear test P = 0.032). When the ratio exceeded 0.83, HOMA-IR significantly decreased with increasing CORT/ACTH ratio (β = 8.36, SE = 3.57, P = 0.027), a trend that persisted after adjusting for confounding factors; ④ Multivariate logistic regression found no independent association between the CORT/ACTH ratio and T2DM risk (adjusted odds ratio, OR = 1.12, 95% confidence interval, CI: 0.39–3.19, P = 0.833), while age was positively associated with T2DM risk, with each 5-year increase in age correlating to a 1.03-fold higher risk (P = 0.023).
Conclusion
The CORT/ACTH ratio exhibits a non-linear relationship with metabolic phenotypes in obese patients,with a significant reduction in HOMA-IR observed at higher ratios.This phenomenon stems from normal HPA axis negative feedback(cortisol elevation accompanied by ACTH suppression,preventing excessive cortisol-induced IR),and this association remains robust after adjusting for baseline triglycerides and LDL-C(supporting its value independent of lipid status).This suggests that the CORT/ACTH ratio may serve as a promising biomarker for metabolic risk stratification,potentially informing precision-based interventions targeting the HPA axis in obesity management.
Springer Science and Business Media LLC
Title: Cortisol/Adrenocorticotropic Hormone Ratio: A Novel Biomarker for Metabolic Risk Stratification in Obese Patients
Description:
Abstract
Objective
This study investigates the predictive value of the cortisol/adrenocorticotropic hormone (CORT/ACTH) ratio, a quantitative marker of hypothalamic-pituitary-adrenal (HPA) axis function, in assessing metabolic heterogeneity and the risk of type 2 diabetes mellitus (T2DM) in obese patients.
By identifying a novel biomarker, this research contributes to metabolic risk stratification and provides a foundation for precise obesity management.
Methods
A retrospective cohort study was conducted involving 210 obese patients (BMI ≥ 28 kg/m²) from the Department of Endocrinology at Jiangsu Second Hospital of Traditional Chinese Medicine, enrolled between September 2022 and September 2023.
Fasting plasma cortisol, adrenocorticotropic hormone (ACTH), and metabolic parameters were measured.
Participants were stratified by tertiles of the CORT/ACTH ratio.
Multivariate logistic regression and restricted cubic spline (RCS) models were used to analyze the associations of the ratio with insulin resistance (IR) and T2DM risk.
Results
①No statistically significant differences were observed among the three groups in gender composition, BMI,homeostasis model assessment of insulin resistance (HOMA-IR), high-density lipoprotein cholesterol (HDL-C), or T2DM prevalence (all P > 0.
05), while age showed a gradient decrease with increasing CORT/ACTH ratio (P = 0.
004); ② Spearman rank correlation analysis revealed that the CORT/ACTH ratio was significantly positively associated with triglycerides (TG, r = 0.
14, P = 0.
036) and low-density lipoprotein cholesterol (LDL-C, r = 0.
19, P = 0.
006), but not with HOMA-IR (r = 0.
05, P = 0.
456);③The RCS model revealed a non-linear relationship between the CORT/ACTH ratio and HOMA-IR (non-linear test P = 0.
032).
When the ratio exceeded 0.
83, HOMA-IR significantly decreased with increasing CORT/ACTH ratio (β = 8.
36, SE = 3.
57, P = 0.
027), a trend that persisted after adjusting for confounding factors; ④ Multivariate logistic regression found no independent association between the CORT/ACTH ratio and T2DM risk (adjusted odds ratio, OR = 1.
12, 95% confidence interval, CI: 0.
39–3.
19, P = 0.
833), while age was positively associated with T2DM risk, with each 5-year increase in age correlating to a 1.
03-fold higher risk (P = 0.
023).
Conclusion
The CORT/ACTH ratio exhibits a non-linear relationship with metabolic phenotypes in obese patients,with a significant reduction in HOMA-IR observed at higher ratios.
This phenomenon stems from normal HPA axis negative feedback(cortisol elevation accompanied by ACTH suppression,preventing excessive cortisol-induced IR),and this association remains robust after adjusting for baseline triglycerides and LDL-C(supporting its value independent of lipid status).
This suggests that the CORT/ACTH ratio may serve as a promising biomarker for metabolic risk stratification,potentially informing precision-based interventions targeting the HPA axis in obesity management.
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